Multivariate Statistical Methods
eBook - ePub
Available until 3 Feb |Learn more

Multivariate Statistical Methods

A Primer, Fourth Edition

  1. 253 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub
Available until 3 Feb |Learn more

Multivariate Statistical Methods

A Primer, Fourth Edition

About this book

Multivariate Statistical Methods: A Primer provides an introductory overview of multivariate methods without getting too deep into the mathematical details. This fourth edition is a revised and updated version of this bestselling introductory textbook. It retains the clear and concise style of the previous editions of the book and focuses on examples from biological and environmental sciences. The major update with this edition is that R code has been included for each of the analyses described, although in practice any standard statistical package can be used.

The original idea with this book still applies. This was to make it as short as possible and enable readers to begin using multivariate methods in an intelligent manner. With updated information on multivariate analyses, new references, and R code included, this book continues to provide a timely introduction to useful tools for multivariate statistical analysis.

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Yes, you can access Multivariate Statistical Methods by Bryan F.J. Manly,Jorge A. Navarro Alberto in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over one million books available in our catalogue for you to explore.

Information

Table of contents

  1. Cover
  2. Half Title
  3. Title Page
  4. Copyright Page
  5. Dedication
  6. Contents
  7. Preface
  8. Authors
  9. Chapter 1 The material of multivariate analysis
  10. Chapter 2 Matrix algebra
  11. Chapter 3 Displaying multivariate data
  12. Chapter 4 Tests of significance with multivariate data
  13. Chapter 5 Measuring and testing multivariate distances
  14. Chapter 6 Principal components analysis
  15. Chapter 7 Factor analysis
  16. Chapter 8 Discriminant function analysis
  17. Chapter 9 Cluster analysis
  18. Chapter 10 Canonical correlation analysis
  19. Chapter 11 Multidimensional scaling
  20. Chapter 12 Ordination
  21. Chapter 13 Epilogue
  22. Index